Background High intensity treatments such as hematopoietic cell transplantation (HCT) can be curative for patients with hematologic malignancies, but this needs to be balanced by the high risk of nonrelapse mortality (NRM) during the first 2 years after HCT. Sarcopenia (low muscle mass) is associated with physical disability and premature mortality in individuals with nonmalignant diseases and may be a predictor of NRM and poor overall survival in patients undergoing HCT. Methods This was a retrospective cohort study of 859 patients with acute leukemia or myelodysplastic syndrome who underwent a first HCT as adults (≥18 years) between 2007 and 2014. Sarcopenia was assessed from pre-HCT abdominal computed tomography scans. Two-year cumulative incidence of NRM was calculated, with relapse/progression considered as a competing risk event. Fine-Gray subdistribution hazard ratio estimates and 95% confidence intervals (CI) were obtained and adjusted for relevant covariates. Kaplan-Meier method was used to examine overall survival. All statistical tests were two-sided. Results Median age at HCT was 51 years (range = 18–74 years); 52.5% had a high [≥3] HCT-comorbidity index; 33.7% had sarcopenia pre-HCT. Sarcopenia was an independent predictor of higher NRM risk (hazard ratio = 1.58, 95% CI = 1.16 to 2.16) compared with patients who were not. The 2-year incidence of NRM approached 30% in patients with sarcopenia and high (≥3) HCT-comorbidity index. Patients with sarcopenia had on average a longer hospitalization (37.2 days vs 31.5 days, P < .001) and inferior overall survival at 2 years (55.2%, 95% CI = 49.5% to 61.0% vs 66.9%, 95% CI = 63.0% to 70.8%, P < .001). Conclusions Sarcopenia is an important and independent predictor of survival after HCT, with potential additional downstream impacts on health-economic outcomes. This information can be used to facilitate treatment decisions prior to HCT and guide interventions to decrease the risk of treatment-related complications after HCT.

Introduction: Chimeric antigen receptor T cell (CAR-T) therapy is an effective treatment for patients with relapsed/refractory diffuse large B cell lymphoma (DLBCL) or other B-cell lymphomas. However, the potent anti-lymphoma effect of CAR-T is balanced by the risk of acute toxicities, namely cytokine release syndrome (CRS) and Immune effector cell-Associated Neurotoxicity Syndrome (ICANS), as well as the variable length of progression-free survival (PFS) after CAR-T. Tools to better risk-stratify for adverse outcomes and to guide targeted interventions are lacking. Sarcopenia (loss of lean muscle mass) is an important cause of age-related functional decline in the general population and is an independent predictor of health outcomes in patients with solid and hematologic cancers, irrespective of age or comorbidity. Advances in software technology have facilitated the near real-time integration of body composition measurements into imaging studies obtained as part of standard clinical care. To date, there have been no studies to examine the association between sarcopenia and outcomes after CAR-T therapy. Methods: Using a retrospective cohort design, 280 consecutive patients with DLBCL or B-cell lymphoma, age ≥18y, and treated with CAR-T therapy between 2015 to 2020 at a single center were included in the study. This analysis was restricted to 226 (80.7%) patients with available computed tomography scans ≤60d from CAR-T. Skeletal muscle area was ascertained from abdominal scans using an automatic image analysis software (APACS; Voronoi Health Analytics; Vancouver, Canada); 3rd lumbar vertebra was used as a landmark because of its high correlation with whole-body muscle mass (J Clin Oncol 2016 34:1339); Figure. Trained researchers blinded to patient demographics and outcomes manually validated these measurements (SliceOmatic; Tomovision; Quebec, Canada). Skeletal muscle index (SMI) was calculated as the ratio of skeletal muscle area (cm 2) divided by height (m). Sarcopenia was defined according to sex-based cutoffs (lowest SMI tertile). Kaplan-Meier method was used to examine PFS at one-year. Multivariable regression was used to calculate the hazard ratio (HR) for PFS and odds ratio (OR) for toxicities with 95% confidence intervals (CI), adjusted for covariates (demographics [age, race/ethnicity], disease characteristics [largest lymph node diameter, blood lactate dehydrogenase], CAR-T product, ECOG performance status). Results: Median age at CAR-T was 63y (range: 18-84); 65.9% were male; 50.9% were non-Hispanic white; 8.8% had ECOG ≥2; 80.5% had a diagnosis of DLBCL; CAR-T products: axicabtagene ciloleucel (51.3%), lisocabtagene maraleucel (31.9%), other (16.8%); 46.9% were treated on a clinical trial; median residual lymph node diameter prior to CAR-T was 2.3cm (range: 0-17.2); 8.0% underwent HCT &lt;1 year after CAR-T and follow-up was censored at HCT. Outcomes: 59.1% developed CRS (18.2% grade ≥2) and 30.1% developed ICANS (15.9% grade ≥2). In adjusted analyses, the odds of developing CRS or ICANS was 1.9-fold (CRS: 1.89 [95%CI: 1.02-3.5], ICANS: 1.93 [1.06-3.51]) higher among patients who were sarcopenic (reference: normal body composition). Average length of hospitalization was also longer (25.6d vs. 21.9d; p=0.037) among patients with sarcopenia. Survival: One-year PFS for the overall cohort was 50.1% (±4.2); PFS was significantly worse for patients who were sarcopenic compared to those with normal muscle mass (35.1% [±6.2] vs. 57.7% [±4.3], p=0.005; Figure). In adjusted analyses, sarcopenia was associated with inferior one-year PFS (HR=1.73 [CI: 1.12-2.68]) compared to those with normal muscle mass. Conclusion: Sarcopenia is an important and independent predictor of outcomes after CAR-T with potential downstream health-economic consequences, including increased burden of acute toxicities and prolonged length of hospitalization. Taken together, these data form the basis for real-time decision making prior to CAR-T (e.g. pre-habilitation, consideration of alternative treatments), or during/shortly after CAR-T (e.g. increased supportive care, rehabilitation), setting the stage for innovative strategies to improve outcomes after CAR-T therapy. Figure 1 Figure 1. Disclosures Artz: Radiology Partners: Other: Spouse has equity interest in Radiology Partners, a private radiology physician practice. Budde: Merck, Inc: Research Funding; Amgen: Research Funding; Astra Zeneca: Research Funding; Mustang Bio: Research Funding; Novartis: Consultancy; Gilead: Consultancy; Roche: Consultancy; Beigene: Consultancy. Herrera: Merck: Consultancy, Research Funding; Gilead Sciences: Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; AstraZeneca: Consultancy, Research Funding; Karyopharm: Consultancy; Kite, a Gilead Company: Research Funding; Seagen: Consultancy, Research Funding; ADC Therapeutics: Consultancy, Research Funding; Takeda: Consultancy; Tubulis: Consultancy; Genentech: Consultancy, Research Funding. Popplewell: Novartis: Other: Travel; Pfizer: Other: Travel; Hoffman La Roche: Other: Food. Shouse: Kite Pharmaceuticals: Speakers Bureau; Beigene Pharmaceuticals: Honoraria. Siddiqi: Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Juno therapeutics: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BeiGene: Other: DSM Member, Speakers Bureau; PCYC: Speakers Bureau; Jannsen: Speakers Bureau; Dava Oncology: Honoraria; ResearchToPractice: Honoraria. Forman: Lixte Biotechnology: Consultancy, Current holder of individual stocks in a privately-held company; Allogene: Consultancy; Mustang Bio: Consultancy, Current holder of individual stocks in a privately-held company.

Introduction: High intensity treatments such as autologous hematopoietic cell transplantation (HCT) can be curative for patients with relapsed/refractory lymphoma (Hodgkin [HL], non-Hodgkin [NHL]), but this needs to be balanced by the risk of non-relapse mortality (NRM) associated with HCT and potentially sub-optimal disease response with less intensive treatments. Measures of pre-treatment body composition such as quantity and quality of muscle are prognostic in patients with solid tumors, but their association with post-HCT outcomes is unknown. We examined the prognostic significance of muscle depletion prior to HCT, defined by having both low muscle quantity (lumbar skeletal muscle index [SMI]) and quality (muscle attenuation [MA]) on computed tomography (CT) imaging, in a population-based cohort of patients undergoing autologous HCT for lymphoma. Next, we examined the prognostic significance of muscle depletion after HCT in a subset of patients with normal muscle composition prior to HCT, allowing us to examine the impact of change in body composition over time. Methods: 440 consecutive patients with lymphoma, age ≥18y, who underwent a first HCT between 2009 and 2014 at a single institution were included in the study. Measures of muscle quantity (SMI) and quality (MA) were ascertained from pre- and post-HCT abdominal CT scans using image analysis software (SliceOmatic; Tomovision, Quebec, Canada). SMI was calculated as the ratio of skeletal muscle area (cm2) divided by height (m)2. Sex and body mass index (BMI)-specific cutoff values of low SMI and MA were used to identify patients with muscle depletion (J Clin Oncol 2013 31:1539). Measurements were made by trained researchers blinded to patient demographics and HCT outcome (Figure 1); 3rd lumbar vertebra was used as a landmark because of its high correlation with whole-body muscle mass (J Clin Oncol 2016 34:1339). This report is limited to 321 (73%) patients with CT scans performed ≤90 days from HCT. Cumulative incidence of NRM was calculated taking into consideration competing risk of disease-related mortality. Kaplan-Meier method was used to examine overall survival (OS). Multivariable Cox regression analysis was used to calculate the hazard ratio (HR) estimates and 95% confidence intervals (CI), adjusted for relevant covariates (demographics, diagnosis, pre-HCT Karnofsky performance score [KPS] and comorbidity index [HCT-CI]). Results: Sixty-two (19.3%) patients had muscle depletion pre-HCT. Median age at HCT was 53y (range: 18-78); 62.0% were male; 54.0% were non-Hispanic white; Diagnoses: HL (N=84 [26.2%]), NHL (N=237 [73.8%]); KPS ≤80 (N=87 [27.1%]); HCT-CI ≥3 (N=52 [16.2%]). Impact of pre-HCT muscle depletion: Patients with pre-HCT muscle depletion had significantly worse 5-y OS (56.4% vs. 77.8%, p<0.001; Figure 2) and higher NRM (11.4% vs. 5.1%, p=0.05) when compared to those with normal body composition. OS was especially poor for patients who were obese (BMI ≥30 kg/m2) and had muscle depletion (20.0% vs. 77.1%, p<0.001) pre-HCT. Median length of hospitalization was also significantly longer (27d vs. 23d; p=0.03) among patients with muscle depletion. Muscle depletion was associated with a 2.2-fold (HR=2.2 [CI: 1.0-4.5]) risk of NRM and 1.8-fold (HR=1.8 [CI: 1.1-3.1]) risk of all-cause mortality when compared to those with normal body composition. Impact of post-HCT muscle depletion: Among 223 patients with normal body composition prior to HCT, 24 (9.3%) developed muscle depletion after HCT, detected at a median 63d (range 27-165) from HCT. In these patients, there was a 3-fold (HR=3.1 [CI: 1.5-6.4]) risk of all-cause mortality compared to those who maintained normal muscle composition throughout HCT. Conclusion: Muscle depletion is an important and independent predictor of outcomes after HCT, with potential additional downstream impacts on health-economic outcomes such as length of hospitalization and the burden of chronic morbidity in long-term survivors. Taken together, these data form the basis for real-time decision making prior to HCT (e.g. pre-habilitation, less intensive treatment approaches), or during HCT (e.g. dietary optimization, increased supportive care services, resistance training), setting the stage for innovative strategies to improve outcomes after HCT. Disclosures Chen: Affimed: Research Funding; Merck & Co., Inc.: Consultancy, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Research Funding; Seattle Genetics: Consultancy, Honoraria, Research Funding, Speakers Bureau; Genentech Inc.: Consultancy; Millennium Pharmaceuticals: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding. Forman:Mustang Therapeutics: Other: Licensing Agreement, Patents & Royalties, Research Funding.

Introduction: Hematopoietic cell transplantation (HCT)-related factors, such as total body irradiation (TBI) used for conditioning, graft-versus-host disease (GvHD), and prolonged exposure to calcineurin-inhibitors, can result in high risk for subsequent skin cancers in long-term survivors. Previous studies examining skin cancers after HCT have largely focused on patients transplanted in earlier eras (<2000), which may not be as informative for providers caring for survivors treated with contemporary conditioning (e.g. less myeloablative) approaches or GvHD treatment regimens, and do not account for newer stem cell sources (e.g. cord, haploidentical) with their evolving immunosuppression risk. Additionally, due to registry reporting, past studies have largely focused on melanoma, which underestimates the burden due to more common skin cancers such as squamous cell carcinoma (SCC) and basal cell carcinoma (BCC). The current study describes the incidence and risk factors of melanoma and non-melanoma skin cancer in a large contemporary cohort of HCT survivors. Methods: 2338 consecutive patients who underwent a first HCT between 2005 and 2014 at City of Hope (COH) and survived ≥1 year, were included in the study. Patients with a history of skin cancer prior to HCT were excluded from the cohort. All skin cancers were validated using pathology reports, and physician notes (20%) whenever the former was not available. Skin cancers included SCC, BCC, melanoma, atypical fibroxanthoma, and merkel cell carcinoma. Patients were followed from HCT to death, second HCT, last known alive date, or December 31, 2018, whichever occurred first. Cumulative incidence of skin cancer was estimated taking into consideration competing risk of death. Fine-Gray sub-distributional hazard regression was used to calculate hazard ratio (HR) estimates, adjusted for relevant covariates. Results: Median age at HCT was 51.8y (range: 0.7-78.7); 57.6% were male; 56.5% were non-Hispanic white (NHW); 4.4% had a history of Pre-HCT cancer (antecedent to primary diagnosis); 47.7% underwent allogeneic HCT; 22.0% received myeloablative TBI (≥1200 cGy)-based conditioning. Among survivors of allogeneic HCT, 57.2% developed ≥moderate chronic GvHD (84% involving the skin); the most common immunosuppressive agents used for the management of ≥moderate chronic GvHD were tacrolimus (84.6%), followed by sirolimus (76.5%), and cyclosporine (28.4%). Burden of skin cancer over time: 179 survivors developed a total of 450 skin cancers after HCT; median time from HCT to first skin cancer was 2.8 years (range: 0.2-13.6). SCC was the most common subtype (59.1%), followed by BCC (31.3%), melanoma (5.1%), and other (4.4%); 43.4% of patients with SCC had invasive or high grade disease at presentation. The cumulative incidence of de novo skin cancer after HCT was 8.3% at 5 years, and 14.8% at 10 years (figure). Eighty-nine patients with skin cancer had a second skin cancer at a median of 0.5 years (range: 0.2 to 7.2) from the first; 55.1% were of a different histology. The cumulative incidence of a second skin cancer was 41.9% at 5-years (figure). Risk factors: Multivariate analysis revealed male sex (HR=1.7, p=0.0008), NHW race/ethnicity (HR=9.0, p<0.0001), older age HCT (≥50years at HCT, HR=2.4, p<0.0001), allogeneic HCT (HR=2.2, p<0.0001), and a history non-skin cancer prior to HCT (HR=1.7, p=0.04) to be significant and independent predictors of post-HCT skin cancer risk. Among allogeneic HCT patients, neither severity of chronic GvHD, location (e.g. skin), nor duration of post-HCT immunosuppression were associated with risk of de novo skin cancer, irrespective of skin cancer histology. Conclusions: This study confirms the higher risk of skin cancer by sex, race/ethnicity, and age at HCT, and highlights the greater than two-fold risk of skin cancer among allogeneic HCT survivors compared to autologous patients, a finding that is not entirely explained by GvHD and its treatment. Further, we identified a previously unreported association between pre-HCT (non-skin) cancer and post-HCT cancer risk, and describe the very high burden of multiple histologically distinct skin cancers over time. Taken together, these data set form the basis for implementation of updated risk-based screening and prevention practices in survivors at highest risk of skin cancer after HCT. Disclosures Abdulla: Johnson & Johnson: Research Funding; Elorac: Research Funding; Trillium: Research Funding; Stemline: Research Funding; MiRagen: Research Funding; Bionz: Research Funding; Mallinckrodt: Research Funding; Mallinckrodt: Consultancy; Mallinckrodt: Speakers Bureau. Nakamura:Merck: Membership on an entity's Board of Directors or advisory committees; Celgene: Other: support for an academic seminar in a university in Japan; Alexion: Other: support to a lecture at a Japan Society of Transfusion/Cellular Therapy meeting ; Kirin Kyowa: Other: support for an academic seminar in a university in Japan.